• aggregate_impute() handles the corner case when join results in an empty dataset.
  • The model_fun argument of model_impute() can be either a function or a string containing the name of a function (like "glm"). Include the package name in case the function is not available in base R (like "INLA::inla").
  • impute() gains an extra argument. Use it for observations not in the model that you still want to add in the follow-up analysis. For example: exclude rare observations from the model but you want them in the aggregations.
  • impute() on INLA models now also handles the binomial, the zero-inflated Poison (type 0 and 1) and the zero-inflated negative binomial (type 0 and 1) distributions.
  • Add hurdle_impute() to fit a hurdle model based on a model of the presences and a model of the counts.
  • Added validation rules for rawImputed and aggregatedImputed objects.
  • Update checklist infrastructure.